Update app.py

app.py

@@ -14,7 +14,7 @@ with open('loras.json', 'r') as f:
     loras = json.load(f)
 
 # Initialize the base model
-base_model = "AlekseyCalvin/MYTHSTOIC_color_Diffusers"
+base_model = "AlekseyCalvin/AlekseyCalvin/Mythstic_Color_Soonr_Flux"
 pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
 
 MAX_SEED = 2**32-1
@@ -115,7 +115,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=css) as app:
     )
     	    # Info blob stating what the app is running
     info_blob = gr.HTML(
-        """<div id="info_blob"> Img. Manufactory Running On: Our 'MytHSTic Color SOON®' Fast (4-8 step) FLUX Schnell-Base Model (at AlekseyCalvin/MYTHSTOIC_color_Diffusers). Now testing related LoRAs (#s2-8,11,12,14,16)for merging. </div>"""
+        """<div id="info_blob"> Img. Manufactory Running On: Our 'MytHSTic Color SOON®' Fast (4-8 step) FLUX Schnell-Base Model (at AlekseyCalvin/Mythstic_Color_Soonr_Flux). Now testing HST-triggered historic photo LoRAs (#s2-8,11,12,14,16)for training-eval & merging. </div>"""
     )
 
         # Info blob stating what the app is running
@@ -146,8 +146,8 @@ with gr.Blocks(theme=gr.themes.Soft(), css=css) as app:
         with gr.Accordion("Advanced Settings", open=True):
             with gr.Column():
                 with gr.Row():
-                    cfg_scale = gr.Slider(label="CFG Scale", minimum=0, maximum=20, step=.5, value=3.5)
-                    steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=20)
+                    cfg_scale = gr.Slider(label="CFG Scale", minimum=0, maximum=20, step=.5, value=0)
+                    steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=5)
                 
                 with gr.Row():
                     width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=768)